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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

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2018 Impact Factor: 1.205

Front Earth Sci    0, Vol. Issue () : 83-94    https://doi.org/10.1007/s11707-011-0189-7
RESEARCH ARTICLE
Evaluation of sediment yield in PSIAC and MPSIAC models by using GIS at Toroq Watershed, Northeast of Iran
Mohammad Reza Mansouri Daneshvar1, Ali Bagherzadeh2()
1. Department of Geography, Mashhad Branch, Islamic Azad University, Mashhad, Iran; 2. Department of Agriculture, Mashhad Branch, Islamic Azad University, Mashhad, Iran
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Abstract

Regarding the importance of watersheds in arid and semi-arid regions, it is necessary to better protect water supplies such as dam reservoirs. The most efficient way of conserving water sources is to apply proper management to decrease erosion and sedimentation. The first step of this process is to be aware of sediment yield (Qs)/production and identify erosive zones in upper reach of reservoirs. The present study aims to evaluate Qs and production in Pacific Southwest Inter-Agency Committee (PSIAC) and modified PSIAC (MPSIAC) models by using satellite data, GIS analysis, and field observations. According to the results, the study area can be categorized into five erosive classes: very high, high, moderate, low and negligible. The east part of the watershed is slightly eroded due to its hard surface geology and relatively flat topography characteristics, while the northern and southern parts of the basin are highly eroded because of the high erodibility potential of soil and intensive cultivation of the area. A comparison of the output maps from PSIAC and MPSIAC models showed that the calculated Qs in most parts correspond well in both models and with field observations. The results of regression between main determining factors (surface geology, soil, topography and land cover) and Qs derived from each model indicated moderate to strong correlation coefficient (R2 = 0.436-0.996 to 0.893-0.998) after PSIAC and MPSIAC models, respectively.

Keywords evaluation of sediment yield (Qs)      erodible factors      Pacific Southwest Inter-Agency Committee (PSIAC) and modified PSIAC (MPSIAC) models      sediment production      GIS      Toroq Watershed      Northeast of Iran     
Corresponding Author(s): Bagherzadeh Ali,Email:abagher_ch@yahoo.com   
Issue Date: 05 March 2012
 Cite this article:   
Mohammad Reza Mansouri Daneshvar,Ali Bagherzadeh. Evaluation of sediment yield in PSIAC and MPSIAC models by using GIS at Toroq Watershed, Northeast of Iran[J]. Front Earth Sci, 0, (): 83-94.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-011-0189-7
https://academic.hep.com.cn/fesci/EN/Y0/V/I/83
Fig.1  Location and geographical position of the study area
Fig.2  Satellite image (a), surface geology (b), soil and land units (c) and isohyet map (d) of the study area
No.FactorR
1Surface geology0-10
2Soil0-10
3Climate0-10
4Runoff0-10
5Topography0-20
6Land cover-10-10
7Land use-10-10
8Upland erosion0-25
9Channel erosion0-25
Tab.1  Effective factors on erosion and and their ranking values in PSIAC model
Sediment classQualitative categoryRQs/(m3·km-2·a-1)
5Severe100-150>1450
4Heavy75-100450-1450
3Moderate50-75250-450
2Slight25-5095-250
1Very slight0-25<95
Tab.2  Sediment class and after total ranking values of nine factors in PSIAC and MPSIAC models
Fig.3  Isotherm map (a), runoff potential (b), topography and elevation (c) and land slope map (d) of the study area
Fig.4  Land cover (a), land use (b), upland erosion potential (c) and channel erosion potential (d) of the study area
FactorClassAttributionsPSIAC
SymbolScore
Surface geology1Granite, leucogranite, ultrabasic rocksX10
2Quartz conglomerate0
3Dolomite, crystallized limestone2
4Sandstone, shale, conglomerate6
5Shale and phylite8
6Quaternary terraces, fault lines10
Soils1Mountains types, entisolsX22
2Hills types, aridisols5
3Other types2
Climate1Annual precipitation 250-300 mm, annual temperature 13°C-15°CX30
2Annual precipitation 300-350 mm, annual temperature 11°C-13°C5
3Annual precipitation 350-400 mm, annual temperature 9°C-11°C10
Runoff1Low and negligible flood potentialX45
2Moderate and high flood potential8
Topography10Slope less than 5°, altitude less than 1400 mX56
2Slope 5°-15°, altitude 1400-2000 m12
3Slope more than 15°, altitude more than 2000 m18
Land cover1Scattered pasture land, dry farmingX68
2Residential area, gravelly river bed0
3Semi compact pasture land-4
4Irrigated farming and garden-7
5Compact pasture land-10
Land use1Cultivated landX78
2Villages and roads0
3Planted land-7
4Other lands-10
Upland erosion10Lowly erodible surfaceX85
2Moderate erodible surface12
3Highly erodible surface20
Channel erosion1Main stream and erosive channelX920
2Minor branches, lands without streams2
Tab.3  Attributions of nine factors and scores by the PSIAC model at the study area
FactorClassAttributionsMPSIAC
SymbolScore
Surface geology1Granite, leucogranite, ultrabasic rocksY10
2Quartz conglomerate0
3Dolomite, crystallized limestone2
4Sandstone, shale, conglomerate6
5Shale and phylite8
6Quaternary terraces, fault lines10
Soils1Sandy loam, high permeability, OM<1%Y22.33
2Silt loam, low permeability, OM 1%-2%,8.33
3Solid field lands and massive soils, OM<1%1.66
Climate16-hour rainfall with 2-year frequency 10 mmY32
26-hour rainfall with 2-year frequency 20 mm4
36-hour rainfall with 2-year frequency 25 mm5
Runoff1Annual runoff 30mm, yield of specific flood peak 0.2 mmY42.18
2Annual runoff 80mm, yield of specific flood peak 0.7 mm7.48
Topography1Average of slope 5%Y51.65
2Average of slope 10%3.30
3Average of slope 30%9.90
Land cover1Bare ground 60%Y612
2Bare ground 50%10
3Bare ground 40%8
4Bare ground 30%6
5Bare ground 20%4
Land use1Canopy covering 25%Y715
2Canopy covering 5%19
3Canopy covering 65%7
4Canopy covering 45%11
Upland erosion1Lowly erodible surfaceY83.25
2Moderate erodible surface8.75
3Highly erodible surface14.25
Channel erosion1Main stream and erosive channelY918.37
2Minor branches, lands without streams3.34
Tab.4  Attributions of nine factors and scores by the MPSIAC model at the study area
Sediment classQualitative categoryPSIACMPSIAC
Qs/(m3·km-2·a-1)Sediment production (S)/(m3·a-1)Soil losses (T)/(m3·km-2·a-1)Qs/(m3·km-2·a-1)Sediment production (S)/(m3·a-1)Soil losses (T) /(m3·km-2·a-1)
5Very high1987.711590.1712423.191067.141782.136669.65
4High828.6853805.935179.22433.9173430.432711.93
3Moderate345.4759442.412159.22176.4338259.001102.69
2Low144.0320267.68900.1871.74461.99448.36
1Negligible60.05941.51375.2829.170.00182.31
Total-3365.93136047.7021037.091778.39113933.5611114.95
Mean-673.1927209.544207.42355.6822786.712222.99
Tab.5  , total sediment production and soil losses of each sediment class at the study area resulted from PSIAC and MPSIAC models
Sediment classQualitative categoryAverage of total ranking value(R)/(m3·km-2·a-1)Area of each sediment class
PSIACMPSIAC
km2%km2%
5Very high112.50.800.201.670.42
4High87.564.9316.47169.2342.93
3Moderate62.5172.0643.65216.8555.01
2Low37.5140.7235.706.441.63
1Negligible12.515.683.980.000.00
Total basin--394.19100394.19100
Tab.6  Average of total ranking values, the area and the percentage of each sediment class from total surface area, resulted from PSIAC and MPSIAC models
ModelStatistical analyzeTopographySoilSurface geologyLand cover
PSIACPearson correlation (R)0.6600.9920.9510.998*
R20.4360.9840.9040.996
Sig. (2-tailed)0.5410.0810.2000.040
MPSIACPearson correlation (R)0.9600.9450.9830.999**
R20.9220.8930.9660.998
Sig. (2-tailed)0.1800.2120.1170.005
Tab.7  Correlation between PSIAC and MPSIAC models with main determining factors (surface geology, soil, topography and land cover) on annual at the study area
Fig.5  zoning based on PSIAC (a) and MPSIAC (b) models at the study area
Fig.6  Sediment classes and percentage of each sediment class from total sediment production resulted from PSIAC and MPSIAC models
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